engleski

Applying the Bayesian method for evaluating uncertainty in mass calibration

The procedure for evaluating measurement uncertainty by applying the Bayesian method is described in the paper. The Bayesian method differs from the MCS method and GUM method for evaluating the measurement uncertainty. The Bayesian method combines prior knowledge about the measurand with the data collected during the calibration process. The best estimate and coverage interval for the measurand can be calculated from the joint posterior probability distribution obtained from the combination mentioned above. In addition to this, the GUM method, MCS method, and Bayesian method for evaluating the measurement uncertainty are compared for the mass calibration model. It proved that all three methods give the similar results when the Bayesian method is conducted under the noninformative prior distribution.

Uncertainty propagation ; Bayesian method ; prior distribution ; posterior distribution ; MC method ; GUM method

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